4.7 Article

Passive MIMO Radar Detection with Unknown Colored Gaussian Noise

Journal

REMOTE SENSING
Volume 13, Issue 14, Pages -

Publisher

MDPI
DOI: 10.3390/rs13142708

Keywords

radar detection; passive radar; colored Gaussian noise; generalized likelihood ratio test; multiple-input multiple-output

Funding

  1. National Natural Science Foundation of China [61671352]
  2. National Key R&D Program of China [2018YFB2202500]
  3. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [61621005]

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This paper investigates target detection of passive MIMO radar with multiple illuminators of opportunity and receivers. A generalized likelihood ratio test is proposed for the radar, which is applicable for cases with unknown covariance matrix of colored noise. Numerical examples verify the effectiveness of the proposed method.
The target detection of the passive multiple-input multiple-output (MIMO) radar that is comprised of multiple illuminators of opportunity and multiple receivers is investigated in this paper. In the passive MIMO radar, the transmitted signals of illuminators of opportunity are totally unknown, and the received signals are contaminated by the colored Gaussian noise with an unknown covariance matrix. The generalized likelihood ratio test (GLRT) is explored for the passive MIMO radar when the channel coefficients are also unknown, and the closed-form GLRT is derived. Compared with the GLRT with unknown transmitted signals and channel coefficients but a known covariance matrix, the proposed method is applicable for a more practical case whenthe covariance matrix of colored noise is unknown, although it has higher computational complexity. Moreover, the proposed GLRT can achieve similar performance as the GLRT with the known covariance matrix when the number of training samples is large enough. Finally, the effectiveness of the proposed GLRT is verified by several numerical examples.

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